Population-Contrastive-Divergence: Does consistency help with RBM training?

Oswin Krause; Asja Fischer; Christian Igel

doi:10.1016/j.patrec.2017.11.022

Population-Contrastive-Divergence: Does consistency help with RBM training?

Oswin Krause, Asja Fischer, Christian Igel

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9 Citations (Scopus)

Original language	English
Journal	Pattern Recognition Letters
Volume	102
Pages (from-to)	1-7
ISSN	0167-8655
DOIs	https://doi.org/10.1016/j.patrec.2017.11.022
Publication status	Published - 15 Jan 2018

Keywords

Restricted Boltzmann machine
Markov chain Monte Carlo
Contrastive divergence
Population Monte Carlo

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10.1016/j.patrec.2017.11.022

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@article{e0cef4723432457ba3583861fcd1b973,

title = "Population-Contrastive-Divergence: Does consistency help with RBM training?",

keywords = "Restricted Boltzmann machine, Markov chain Monte Carlo, Contrastive divergence, Population Monte Carlo",

author = "Oswin Krause and Asja Fischer and Christian Igel",

year = "2018",

month = jan,

day = "15",

doi = "10.1016/j.patrec.2017.11.022",

language = "English",

volume = "102",

pages = "1--7",

journal = "Pattern Recognition Letters",

issn = "0167-8655",

publisher = "Elsevier BV * North-Holland",

}

TY - JOUR

T1 - Population-Contrastive-Divergence

T2 - Does consistency help with RBM training?

AU - Krause, Oswin

AU - Fischer, Asja

AU - Igel, Christian

PY - 2018/1/15

Y1 - 2018/1/15

KW - Restricted Boltzmann machine

KW - Markov chain Monte Carlo

KW - Contrastive divergence

KW - Population Monte Carlo

U2 - 10.1016/j.patrec.2017.11.022

DO - 10.1016/j.patrec.2017.11.022

M3 - Journal article

SN - 0167-8655

VL - 102

SP - 1

EP - 7

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

ER -